Audio processing applications often apply digital signal processing (“DSP”) operations that intentionally modify the audio content of an audio track. These operations typically cause audio events in the audio data to have an effect in the audio presentation for an extended period of time. In other words, certain DSP operations can cause an audio event to leave a trailing sound effect in the audio presentation even after the event finishes. Such a sound effect affects the audio presentation in the absence of a subsequent audio event. It also affects the sound generated during a subsequent audio event. Accordingly, audio processing applications need to account for the temporal effects that can result from applying certain signal processing operations on audio data. To account for such temporal effects on audio data that is within a particular interval of a track, audio processing applications need to consider audio data before and/or after the particular interval.
Audio processing applications also re-encode audio data. Re-encoding audio data might entail re-sampling the audio data, reducing the number of audio samples, increasing the number of audio samples, changing the encoding format for the audio samples, etc. When such applications re-encode an interval of an audio track, they often need to account for certain number of samples before and after the interval, because of the temporal nature of audio data.
Accordingly, in a variety of contexts, audio processing applications need to account for the effects of audio data that is before and/or after a particular segment of audio data that the applications are processing. For such contexts, there is a need in the art for a method that efficiently accounts for the temporal nature of audio processing.